SCARF
Single-cell RNA+ATAC foundation model pretrained on >2.7M cells for multimodal representation, matching, cross-omics translation, and few-shot annotation.
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- Computational Biology
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- 2026-10-10
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EpiFoundation doi.org
Foundation model for scATAC-seq using peak-to-gene aligned pretraining for cell representation, annotation, batch correction, and gene-expression prediction.
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Atacformer doi.org
Transformer foundation model for scATAC-seq that learns embeddings of cis-regulatory elements for clustering, annotation, and reference mapping.
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CAPTAIN doi.org
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scATAC-seq foundation model pretrained on ~5M cells and >35B tokens for representation learning, annotation, imputation, perturbation prediction, and in-silico cCRE knockout.
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scArches github.com
Transfer learning framework for mapping new single-cell datasets onto pre-trained reference atlases across batches, conditions, and modalities.
Computational Biology › Machine Learning Tasks and Models > Foundation Models > Single-Cell Epigenomics Foundation Models: “Single-cell RNA+ATAC foundation model pretrained on >2.7M cells for multimodal representation, matching, cross-omics translation, and few-shot annotation.”